Nikki Haley
Article
Nikki Haley is a recurring person in the Astral Codex Ten archive, appearing 3 times across 3 issues between February 25, 2021 and February 20, 2024. The archive places it in contexts such as “success stories like … Nikki Haley”; “Our candidates who have qualified today are Nikki Haley”; “MODERATOR: Thank you, Chris Christie. Our next question is for Nikki Haley”. It most often appears alongside Democrats, Donald Trump, Elon Musk.
Metadata
- Category: People
- Mention count: 3
- Issue count: 3
- First seen: February 25, 2021
- Last seen: February 20, 2024
Appears In
Related Pages
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- Democrats (2 shared issues)
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- Donald Trump (2 shared issues)
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- Elon Musk (2 shared issues)
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- Iowa (2 shared issues)
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- Israel (2 shared issues)
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- Trump (2 shared issues)
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- Twitter (2 shared issues)
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- Ukraine (2 shared issues)
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- 2024 presidential election (1 shared issues)
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- Aella (1 shared issues)
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- AI (1 shared issues)
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- Akron (1 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
It could appeal to blacks and Hispanics. They’re mostly working-class, so they hate the elites as much as anyone else. So far the left has kept them voting Democrat by scaring them with stories about how racist the white working class is, and convincing them that only Democratic elites can keep them safe. Your job is to make the Marxist argument that this is the typical ruling class tactic of using racial animus to keep the working classes divided and powerless. If you do this right, you can get a bunch of minorities on your side without driving away any whites; mutual enemies are the duct tape of political coalitions. The pro-Trump shift among blacks and Hispanics in 2020 proves that minorities are willing to vote Republican once someone frames the conflict in class terms. And success stories like Ben Carson, Ted Cruz and Nikki Haley prove that white Republicans are friendly to minorities once they're convinced they share their values. All you need to do is drag both sides to the altar and tie the knot.
Our candidates who have qualified today are Chris Christie, Nikki Haley, Ron DeSantis, and Donald Trump. And our first question is: what issue do you think is most important in this election? Chris Christie, let’s start with you.. Your Forbidden Letter is “V”.
MODERATOR: Sorry Chris, there’s a “V” in voters. Our next candidate is Nikki Haley. Nikki, the question is still which issue is most important, and your Forbidden Letter is “K”.
MODERATOR: Thank you, Chris Christie. Our next question is for Nikki Haley. Nikki, what would you do to address the Chrisis . . . sorry, the crisis . . . in Israel and Palestine? Remember, your forbidden letter is still “K”.
Will Nikki Haley win the 2028 presidential election? Answer: 10%
How many residents will live in Prospera, a new special economic zone in Honduras, on Jan 1, 2026? Answer: 600 (80% confidence interval 100-2,000) This seems like a good guess (except that my confidence interval would have included zero because there’s a 20%+ chance that it gets shut down). So overall its forecasts seem pretty impressive. But I was concerned by its reasoning even in some of the questions it got “right”. For example, the Nikki Haley question tried to get a base rate by asking what percent of elections Haley had won before, and found she had won 71% of them - these were mostly elections for South Carolina governor. You can see what the AI is trying to do - but it’s not going to work. Then it got confused and read a lot of news stories about how she’s currently losing the 2024 presidential election, and seemed to think they were about 2028. So either the AI only got a reasonable probability by coincidence, or it was testing many different strategies, throwing out the useless ones, and updating only on the useful ones, in a way that was kind of opaque to the casual reader. Still, if the company says it beats most human forecasters, this doesn’t seem totally impossible based on what I’ve seen. And that would be exciting! An AI that can generate probabilistic forecasts for any question seems like in some way a culmination of the rationalist project. And if you can make something like this work, it doesn’t sound too outlandish that you could apply the same AI to conditional forecasts, or to questions about the past and present (eg whether COVID was a lab leak). I would be most excited if at some point this graduated from its geopolitical focus and was able to answer questions on any topic (eg “what is the chance that Astral Codex Ten gains paid subscribers this year?”), maybe if the questioner gives it links or feeds it some of the appropriate information. FutureSearch is run by a team formerly from Metaculus, including former Metaculus CTO (and Google internal prediction market veteran) Dan Schwarz. They’re looking for potential clients and/or investors; if you’re interested, email hello@futuresearch.ai. Vitalik On AI Prediction Markets Vitalik Buterin, Ethereum-founder-turned-cryptocurrency-public-intellectual, has a blog post on The Promise And Challenge Of Crypto + AI Applications. One of them is a prediction market. He writes: Prediction markets have been a holy grail of epistemics technology for a long time; I was excited about using prediction markets as an input for governance ("futarchy") back in 2014, and played around with them extensively in the last election as well as more recently. But so far prediction markets have not taken off too much in practice, and there is a series of commonly given reasons why: the largest participants are often irrational, people with the right knowledge are not willing to take the time and bet unless a lot of money is involved, markets are often thin, etc. One response to this is to point to ongoing UX improvements in Polymarket or other new prediction markets, and hope that they will succeed where previous iterations have failed. After all, the story goes, people are willing to bet tens of billions on sports, so why wouldn't people throw in enough money betting on US elections or LK99 that it starts to make sense for the serious players to start coming in? But this argument must contend with the fact that, well, previous iterations have failed to get to this level of scale (at least compared to their proponents' dreams), and so it seems like you need something new to make prediction markets succeed. And so a different response is to point to one specific feature of prediction market ecosystems that we can expect to see in the 2020s that we did not see in the 2010s: the possibility of ubiquitous participation by AIs. AIs are willing to work for less than $1 per hour, and have the knowledge of an encyclopedia - and if that's not enough, they can even be integrated with real-time web search capability. If you make a market, and put up a liquidity subsidy of $50, humans will not care enough to bid, but thousands of AIs will easily swarm all over the question and make the best guess they can. The incentive to do a good job on any one question may be tiny, but the incentive to make an AI that makes good predictions in general may be in the millions. Note that potentially, you don't even need the humans to adjudicate most questions: you can use a multi-round dispute system similar to Augur or Kleros, where AIs would also be the ones participating in earlier rounds. Humans would only need to respond in those few cases where a series of escalations have taken place and large amounts of money have been committed by both sides. This is a powerful primitive, because once a "prediction market" can be made to work on such a microscopic scale, you can reuse the "prediction market" primitive for many other kinds of questions: Is this social media post acceptable under [terms of use]?